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Mathematical Statistics

by Lawrence Leemis

Mathematical foundations for statistical practice

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AlbakiReads Editorial

Mathematical foundations for statistical practice

Lawrence Leemis’s text connects the mathematical basis of statistics with its practical use. Assuming prior study in calculus-based probability, it organizes the subject around random sampling, point estimation, interval estimation, and hypothesis testing. Figures and Monte Carlo experiments in R support the development of intuition, while examples drawn from varied fields show how statistical methods can be applied. More than 300 exercises provide opportunities to work through the concepts, making the book structured for classroom use as well as study.

Good fit for readers who enjoy

  • Students who have completed a calculus-based probability course
  • Learners seeking a structured introduction to estimation and hypothesis testing
  • Instructors looking for a statistics text with extensive exercises and R simulations

Themes

Mathematical statisticsSampling and estimationHypothesis testingStatistical computation in R

Based on publisher information and book metadata.

Book overview

Mathematical Statistics describes the mathematical underpinnings associated with the practice of statistics. The pre-requisite for this book is a calculus-based course in probability. Nearly 200 figures and dozens of Monte Carlo simulation experiments in R help develop the intuition behind the statistical methods. Real-world problems from a wide range of fields help the reader apply the statistical methods. Over 300 exercises are used to reinforce concepts and make this book appropriate for classroom use. The table of contents for this book is:

1. Random Sampling2. Point Estimation3. Interval Estimation4. Hypothesis Testing

 

 

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